Key Responsibilities
Design, develop, and maintain scalable data pipelines using Python and PySpark.
Build and manage ETL/ELT workflows for processing structured and unstructured data.
Develop and optimize Spark applications to handle large-scale datasets efficiently.
Implement cloud-native data solutions using AWS services.
Design and maintain Data Lakes on AWS.
Perform data ingestion from multiple sources including APIs, databases, files, and streaming platforms.
Monitor, troubleshoot, and optimize data workflows for performance and reliability.
Ensure data quality, integrity, security, and governance standards are followed.
Implement automation and orchestration of data workflows using scheduling tools.
Collaborate with cross-functional teams for requirement gathering and solution design.
Conduct code reviews, unit testing, and performance tuning.
Prepare technical documentation and deployment procedures.
Support production incidents and perform root cause analysis.

Mandatory Skills
Robust expertise in Python
Hands-on experience with PySpark
Proficiency in SQL and query optimization

📌 Aws Data Engineer Chennai
🏢 Cognizant
📍 Chennai